Biomedical subjects

Paolo Vicini

Publications and source records attributed to Paolo Vicini.

25 records · Page 2Linked to original sources

PubMed2003

Quantitative magnetic resonance imaging analysis of neovasculature volume in carotid atherosclerotic plaque.

BACKGROUND: Neovasculature within atherosclerotic plaques is believed to be associated with infiltration of inflammatory cells and plaque destabilization. The aim of the present investigation was to determine whether the amount of neovasculature present in advanced carotid plaques can be noninvasively measured by dynamic, contrast-enhanced MRI. METHODS AND RESULTS: A total of 20 consecutive patients scheduled for carotid endarterectomy were recruited to participate in an MRI study. Images were obtained at 15-second intervals, and a gadolinium contrast agent was injected coincident with the second of 10 images in the sequence. The resulting image intensity within the plaque was tracked over time, and a kinetic model was used to estimate the fractional blood volume. For validation, matched sections from subsequent endarterectomy were stained with ULEX and CD-31 antibody to highlight microvessels. Finally, all microvessels within the matched sections were identified, and their total area was computed as a fraction of the plaque area. Results were obtained from 16 participants, which showed fractional blood volumes ranging from 2% to 41%. These levels were significantly higher than the histological measurements of fractional vascular area. Nevertheless, the 2 measurements were highly correlated, with a correlation coefficient of 0.80 (P<0.001). CONCLUSIONS: Dynamic contrast-enhanced MRI provides an indication of the extent of neovasculature within carotid atherosclerotic plaque. MRI therefore provides a means for prospectively studying the link between neovasculature and plaque vulnerability.

Blood Volume↗

PubMed2003

Pharmacodynamics of NN2211, a novel long acting GLP-1 derivative.

OBJECTIVE: To evaluate the effects of NN2211, a GLP-1 derivative, on glucose and insulin homeostasis in healthy volunteers by use of a nonlinear mixed-effects modeling approach. DESIGN: NN2211 is a GLP-1 derivative intended for the treatment of type 2 diabetes. In the present study, eight dose levels of NN2211 were tested in healthy human volunteers. Since NN2211 is only intended to have an effect when glucose levels are above baseline (thus limiting the risk of hypoglycaemia), no effects would be expected in healthy volunteers. In order to demonstrate effect in a phase 1 study including only healthy subjects, a glucose dose was administered i.v. 9 h after NN2211 dosing; the insulin response would then be expected to be improved (higher) in the subjects dosed with NN2211. METHODS: In the present work, the pharmacodynamic glucose and insulin response was modeled by fitting glucose and insulin data simultaneously with a nonlinear model incorporating known carbohydrate regulation mechanisms. After an initial model-building phase, the first-order approximation to the likelihood available in NONMEM was used to model the data. Placebo-dosed subjects were included in the analysis. RESULTS: It was possible to satisfactorily fit both insulin and glucose data simultaneously. The analysis demonstrated a dose proportional effect of NN2211 on the parameters controlling beta cell insulin secretion.

Adult↗

PubMed2003

Pharmacokinetic and pharmacodynamic properties of insulin aspart and human insulin.

The preferred approach to determine the pharmacokinetic (PK) and pharmacodynamic (PD) properties of insulin analogues is the euglycemic glucose clamp. Currently non-compartmental data analytical approaches are used to analyze data. The purpose of the present study is to propose a novel compartmental-model for analysis of data from glucose clamp studies. Data used in this trial only involved 18 of the 20 originally treated subjects. Data was obtained from a crossover trial where 18 healthy subjects each received a single subcutaneous (s.c.) dose of 1.2 nmol/kg (body weight) insulin aspart (IAsp) or 1.2 nmol/kg human insulin (HI) during a euglycemic glucose clamp after overnight fast. Serum insulin and glucose concentrations were measured and the glucose infusion rate (GIR) was adjusted after dosing, to maintain blood glucose near basal levels. Individual model parameters were estimated for IAsp, HI, and the corresponding glucose and GIR data. We found statistically significant differences between most of the HI and IAsp pharmacokinetic parameters, including the sigmoidicity of the time course of absorption (1.5 for HI vs. 2.1 for IAsp (unit less), P = 0.0005, Wilcoxon Signed-rank test), elimination rate constant (0.010 min-1 for HI vs. 0.016 min-1 for IAsp (P = 0.002)). The PD model parameters were mostly not different, except for the rate of insulin action (0.012 min-1 for HI vs. 0.017 min-1 for IAsp (P = 0.03)). The model may provide a framework to account for different PK properties when estimating the PD properties of insulin and insulin analogues in glucose clamp experiments.

Adult↗

PubMed2003

An evaluation of population D-optimal designs via pharmacokinetic simulations.

One goal of large scale clinical trials is to determine how a drug is processed by, and cleared from, the human body [i.e., its pharmacokinetic (PK) properties] and how these PK properties differ between individuals in a population (i.e., its population PK properties). Due to the high cost of these studies and the limited amount of data (e.g., blood samples) available from each study subject, it would be useful to know how many measurements are needed and when those measurements should be taken to accurately quantify population PK model parameters means and variances. Previous studies have looked at optimal design strategies of population PK experiments by developing an optimal design for an individual study (i.e., no interindividual variability was considered in the design), and then applying that design to each individual in a population study (where interindividual variability is present). A more algorithmically and informationally intensive approach is to develop a population optimal design, which inherently includes the assessment of interindividual variability. We present a simulation-based evaluation of these two design methods based on nonlinear Gaussian population PK models. Specifically, we compute standard individual and population D-optimal designs and compare population PK model parameter estimates based on simulated optimal design measurements. Our results show that population and standard D-optimal designs are not significantly different when both designs have the same number of samples per individual. However, population optimal designs allow for sampling schedules where the number of samples per individual is less than the number of model parameters, the theoretical limit allowed in standard optimal design. These designs with a low number of samples per individual are shown to be nearly as robust in parameter estimation as standard D-optimal designs. In the limit of just one sample per individual, however, population D-optimal designs are shown to be inadequate.

AIDS Vaccines↗

PubMed2002

Double isotope tracer method for measuring fractional zinc absorption: theoretical analysis.

Several approaches for estimation of fractional zinc absorption (FZA) by calculating the ratio of oral to intravenous stable isotopic tracer concentrations (at an appropriate time) in urine or plasma after their simultaneous administration have been proposed in the last decade. These simple-to-implement approaches, often referred to as the double isotopic tracer ratio (DITR) method, are more attractive than the classical "deconvolution" method and the more commonly used single-tracer methods based on fecal monitoring and indicator dilution, after oral or intravenous tracer administration, respectively. However, the domain of validity of DITR for measuring FZA has recently been questioned. In this paper, we provide a theoretical justification of the validity of four different "approximate" formulations of the DITR technique by demonstrating mathematically that their accuracy is a consequence of the particular properties of zinc kinetics.

Absorption↗

PubMed2002

Epinephrine effects on insulin-glucose dynamics: the labeled IVGTT two-compartment minimal model approach.

The hyperglycemic effects of epinephrine (Epi) are established; however, the modulation of Epi-stimulated endogenous glucose production (EGP) by glucose and insulin in vivo in humans is less clear. Our aim was to determine the effect of exogenously increased plasma Epi concentrations on insulin and glucose dynamics. In six normal control subjects, we used the labeled intravenous glucose tolerance test (IVGTT) interpreted with the two-compartment minimal model, which provides not only glucose effectiveness (S(G)(2*)), insulin sensitivity (S(I)(2*)), and plasma clearance rate (PCR) at basal state, but also the time course of EGP. Subjects were randomly studied during either saline or Epi infusion (1.5 microg/min). Exogenous Epi infusion increased plasma Epi concentration to a mean value of 2,034 +/- 138 pmol/l. During the stable-label IVGTT, plasma glucose, tracer glucose, and insulin concentrations were significantly higher in the Epi study. The hormone caused a significant (P < 0.05) reduction in PCR in the Epi state when compared with the basal state. The administration of Epi has a striking effect on EGP profiles: the nadir of the EGP profiles occurs at 21 +/- 7 min in the basal state and at 55 +/- 13 min in the Epi state (P < 0.05). In conclusion, we have shown by use of a two-compartment minimal model of glucose kinetics that elevated plasma Epi concentrations have profound effects at both hepatic and tissue levels. In particular, at the liver site, this hormone deeply affects, in a time-dependent fashion, the inhibitory effect of insulin on glucose release. Our findings may explain how even a normal subject may have the propensity to develop glucose intolerance under the influence of small increments of Epi during physiological stress.

Adult↗

PubMed2002

Model-based approaches to biomarker discovery and evaluation: a multidisciplinary integrated review.

The most common use of any mathematical or statistical model in physiology, pathophysiology, or therapy evaluation is to organize all relevant components characterizing the system behavior into a rigorously testable framework. This approach is widely applied both to the study of complex homeostatic paradigms involving endogenous substances and to the evaluation of the kinetics and dynamics of xenobiotics such as toxicants and drugs. In either case, one seeks a quantitative framework of the system that is consistent with known physiology and pharmacology and is "compatible" (in some meaningful sense) with all available data. The models are then evaluated and subjected to identifiability and validity tests and can then be used to estimate unknown parameters of interest, to make predictions about system behavior, to simulate previously unobserved behavior in response to a putative perturbation, and to aid in further experimental design. In a broader context, however, the focus and ultimate goal of this set of methodologies (whether this is explicitly stated or not) lies in understanding the mechanisms of physiology and pathophysiology and measuring the effect of therapeutic interventions through the accurate quantification of biomarkers of interest. In this review, we attempt to bring together under this comprehensive framework more than four decades of investigation on modeling and simulation in the life sciences (in particular, we will concentrate on the areas of pharmacology, physiology, and bioengineering). We demonstrate that such modeling approaches, when appropriately designed and evaluated, have significant potential and can be used to understand the multiple factors of disease progression and response to therapeutic interventions, the most likely causes of variability in population and individual responses to therapy, and the most appropriate timing of treatment administration. Lastly, they may allow estimation and prediction of significant outcomes in feasibility and clinical studies.

Animals↗